code: def create_hparams(flags):
      """Create the model hyperparameters.
  
      Args:
          flags (dict): Dictionary with the model requirements.
  
      Returns:
          HParams: Hyperparameter object.
      """
      init_dict = {
          # data
          "support_quick_scoring": False,
          # models
          "dropout": 0.0,
          "attention_hidden_dim": 200,
          # nrms
          "head_num": 4,
          "head_dim": 100,
          # naml
          "filter_num": 200,
          "window_size": 3,
          "vert_emb_dim": 100,
          "subvert_emb_dim": 100,
          # lstur
          "gru_unit": 400,
          "type": "ini",
          # npa
          "user_emb_dim": 50,
          # train
          "learning_rate": 0.001,
          "optimizer": "adam",
          "epochs": 10,
          "batch_size": 1,
          # show info
          "show_step": 1,
      }
      init_dict.update(flags)
      return HParams(init_dict)
  
file_path: recommenders/recommenders/models/newsrec/newsrec_utils.py
imports: from recommenders.models.deeprec.deeprec_utils import flat_config, HParams, load_yaml
  import random
  import re
label_desc: Use image node_id 3 for calling a global function with example usage: create_hparams(flags) and returns: HParams